Text-to-Image
Diffusers
TensorBoard
diffusers-training
sd3
sd3-diffusers
template:sd-lora
lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use TE2G/aran with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TE2G/aran with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("TE2G/aran") prompt = "A photo of aran knit pullover on a mannequin or torso" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 32e317d5256846c0e813a8f0eb9277b43548717709c1c4fc4f53f5f34b813c27
- Size of remote file:
- 1.11 MB
- SHA256:
- 59a8d951ad23ee13a3ce3f715f4fcbe7f4c94ed995ca665d2aeada40f2d92dae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.